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This project represents an endeavor in the realm of digital twin technology, applied to the design and monitoring of process flowsheets within the scope of Aspentech products. Spearheaded by Bartek Borowinski and Anis Belabbas, the initiative employed a unique combination of drone flyovers and machine learning techniques.

The objective was to create intricate 3D mesh representations of plant topologies, which were then integrated with real-time plant data. This innovative methodology not only accurately captures the complexities of process management but also enhances industrial plant monitoring solutions through dynamic, interactive models.

DURATION

6 months

ROLE

Research Lead

COLLABORATOR

Ary B. & Bartek B.

WEBSITE

Visit site

This project represents an endeavor in the realm of digital twin technology, applied to the design and monitoring of process flowsheets within the scope of Aspentech products. Spearheaded by Bartek Borowinski and Anis Belabbas, the initiative employed a unique combination of drone flyovers and machine learning techniques.

The objective was to create intricate 3D mesh representations of plant topologies, which were then integrated with real-time plant data. This innovative methodology not only accurately captures the complexities of process management but also enhances industrial plant monitoring solutions through dynamic, interactive models.

DURATION

6 months

ROLE

Research Lead

COLLABORATOR

Ary B. & Bartek B.

WEBSITE

Visit site

This project represents an endeavor in the realm of digital twin technology, applied to the design and monitoring of process flowsheets within the scope of Aspentech products. Spearheaded by Bartek Borowinski and Anis Belabbas, the initiative employed a unique combination of drone flyovers and machine learning techniques.

The objective was to create intricate 3D mesh representations of plant topologies, which were then integrated with real-time plant data. This innovative methodology not only accurately captures the complexities of process management but also enhances industrial plant monitoring solutions through dynamic, interactive models.

DURATION

6 months

ROLE

Research Lead

COLLABORATOR

Ary B. & Bartek B.

WEBSITE

Visit site

01

PROBLEM

Facing a 2030 peak in crude profitability, oil & gas companies must pivot refinery operations towards chemicals. The challenge is managing this shift cost-effectively. High-fidelity digital twins, updated with real data, offer a solution by simulating design changes, saving time and money.

02

PROCESS

Define Objectives and Scope. Collect Data and Integration means. Create a basic digital twin model that includes critical components of the refinery process.

Use available open source simulation tools and platforms that can handle high-fidelity models. Incorporate complex refinery operations and use cases for chemical production. Validate the model with experts to ensure its accuracy and reliability.

03

CHALLENGES

Simply put, the oil and gas industry's complexity means that creating a digital twin prototype required comprehensive understanding and modeling of physical assets, processes, and data flows, which is a tall order for a small team.

04

OUTCOMES

The successful prototype demonstrated by our team served as a compelling proof of concept that showcased the potential benefits and value of integrating a high-fidelity digital twin with existing AspenTech products, specifically for transitioning refinery operations towards chemical products.

01

PROBLEM

Facing a 2030 peak in crude profitability, oil & gas companies must pivot refinery operations towards chemicals. The challenge is managing this shift cost-effectively. High-fidelity digital twins, updated with real data, offer a solution by simulating design changes, saving time and money.

02

PROCESS

Define Objectives and Scope. Collect Data and Integration means. Create a basic digital twin model that includes critical components of the refinery process.

Use available open source simulation tools and platforms that can handle high-fidelity models. Incorporate complex refinery operations and use cases for chemical production. Validate the model with experts to ensure its accuracy and reliability.

03

CHALLENGES

Simply put, the oil and gas industry's complexity means that creating a digital twin prototype required comprehensive understanding and modeling of physical assets, processes, and data flows, which is a tall order for a small team.

04

OUTCOMES

The successful prototype demonstrated by our team served as a compelling proof of concept that showcased the potential benefits and value of integrating a high-fidelity digital twin with existing AspenTech products, specifically for transitioning refinery operations towards chemical products.

01

PROBLEM

Facing a 2030 peak in crude profitability, oil & gas companies must pivot refinery operations towards chemicals. The challenge is managing this shift cost-effectively. High-fidelity digital twins, updated with real data, offer a solution by simulating design changes, saving time and money.

02

PROCESS

Define Objectives and Scope. Collect Data and Integration means. Create a basic digital twin model that includes critical components of the refinery process. Use available open source simulation tools and platforms that can handle high-fidelity models. Incorporate complex refinery operations and use cases for chemical production. Validate the model with experts to ensure its accuracy and reliability.

03

CHALLENGES

Simply put, the oil and gas industry's complexity means that creating a digital twin prototype required comprehensive understanding and modeling of physical assets, processes, and data flows, which is a tall order for a small team.

04

OUTCOMES

The successful prototype demonstrated by our team served as a compelling proof of concept that showcased the potential benefits and value of integrating a high-fidelity digital twin with existing AspenTech products, specifically for transitioning refinery operations towards chemical products.

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LAST UPDATED 2024-04-11

"Don't Leave Things In The Fridge"

Spike Spiegel

GMT-05

9:46:37 PM

v1.0.0

LAST UPDATED 2024-04-11

"Don't Leave Things In The Fridge"

Spike Spiegel

GMT-05

9:46:38 PM

v1.0.0

LAST UPDATED 2024-04-11

"Don't Leave Things In The Fridge"

Spike Spiegel

GMT-05

9:46:38 PM